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SBIA
2004
Springer
15 years 4 months ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...
85
Voted
ADMA
2005
Springer
157views Data Mining» more  ADMA 2005»
15 years 4 months ago
Learning k-Nearest Neighbor Naive Bayes for Ranking
Accurate probability-based ranking of instances is crucial in many real-world data mining applications. KNN (k-nearest neighbor) [1] has been intensively studied as an effective c...
Liangxiao Jiang, Harry Zhang, Jiang Su
AIME
2009
Springer
15 years 2 months ago
The Role of Biomedical Dataset in Classification
In this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. We quantify the complexity of a biomedical dataset using five complex...
Ajay Kumar Tanwani, Muddassar Farooq
KDD
2006
ACM
118views Data Mining» more  KDD 2006»
15 years 11 months ago
Maximum profit mining and its application in software development
While most software defects (i.e., bugs) are corrected and tested as part of the lengthy software development cycle, enterprise software vendors often have to release software pro...
Charles X. Ling, Victor S. Sheng, Tilmann F. W. Br...
105
Voted
IJSI
2008
156views more  IJSI 2008»
14 years 11 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker